Professional perspectives on decision making about the long-term care of older people

With the increasing pressure on social and health care resources, professionals have to be more explicit in their decision making regarding the long-term care of older people. This grounded theory study used 19 focus groups and nine semi-structured interviews (99 staff in total) to explore professional perspectives on this decision making. Focus group participants and interviewees comprised care managers, social workers, consultant geriatricians, general medical practitioners, community nurses, home care managers, occupational therapists and hospital discharge support staff. The emerging themes spanned context, clients, families and services. Decisions were often prompted by a crisis, hindering professionals seeking to make a measured assessment. Fear of burglary and assault, and the willingness and availability of family to help were major factors in decisions about living at home. Service availability in terms of public funding for community care, the availability of home care workers and workload pressures on primary care services influenced decision 'thresholds' regarding admission to institutional care. Assessment tools designed to assist decision making about the long-term care of older people need to take into account the critical aspects of individual fears and motivation, family support and the availability of publicly funded services as well as functional and medical needs.

The pitfall with PIT tags: Marking freshwater bivalves for translocation induces short-term behavioural costs

Tagging animals is frequently employed in ecological studies to monitor individual behaviour, for example postrelease survival and dispersal of captive-bred animals used in conservation programmes. While the majority of studies focus on the efficacy of tags in facilitating the relocation and identification of individuals, few assess the direct effects of tagging in biasing animal behaviour. We used an experimental approach with a control to differentiate the effects of handling and tagging captive-bred juvenile freshwater pearl mussels, Margaritifera margaritifera, prior to release into the wild. Marking individuals with passive integrated transponder (PIT) tags significantly decreased their burrowing rate and, therefore, increased the time taken to burrow into the substrate. This effect was contributed to, in part, by the detrimental impacts of handling, which also significantly affected activity, burrowing ability and the time taken for each individual to emerge and start probing the substrate. Disturbance during handling and tagging may lead to indirect mortality after release by increasing the risk of predation or dislodgement during flooding, thereby potentially compromising any conservation strategy contingent on population supplementation or reintroduction. This is the first study to demonstrate that handling and PIT tagging has a detrimental impact on invertebrate behaviour. Moreover, our results provide useful information that will inform freshwater bivalve conservation strategies.

Short, medium and long term load forecasting model and virtual load forecaster based on radial basis neural networks

Artificial neural networks (ANNs) can be easily applied to short-term load forecasting (STLF) models for electric power distribution applications. However, they are not typically used in medium and long term load forecasting (MLTLF) electric power models because of the difficulties associated with collecting and processing the necessary data. Virtual instrument (VI) techniques can be applied to electric power load forecasting but this is rarely reported in the literature. In this paper, we investigate the modelling and design of a VI for short, medium and long term load forecasting using ANNs. Three ANN models were built for STLF of electric power. These networks were trained using historical load data and also considering weather data which is known to have a significant affect of the use of electric power (such as wind speed, precipitation, atmospheric pressure, temperature and humidity). In order to do this a V-shape temperature processing model is proposed. With regards MLTLF, a model was developed using radial basis function neural networks (RBFNN). Results indicate that the forecasting model based on the RBFNN has a high accuracy and stability. Finally, a virtual load forecaster which integrates the VI and the RBFNN is presented.

Micro-environmental change as a trigger for granite decay in offshore Irish lighthouses: implications for the long-term preservation of operational historic buildings.

Following automation of lighthouses around the coastline of Ireland, reports of accelerated deterioration of interior granite stonework have increased significantly with an associated deterioration in the historic structure and rise in related maintenance costs. Decay of granite stone- work primarily occurs through granular disintegration with the effective grusification of granite surfaces. A decay gradient exists within the towers whereby the condition of granite in the lower levels is much worse than elsewhere. The lower tower levels are also regions with highest rela- tive humidity values and greatest salt concentrations. Data indicate that post-automation decay may have been trig- gered by a change in micro-environmental conditions within the towers associated with increased episodes of condensation on stone surfaces. This in turn appears to have facilitated deposition and accumulation of hygro- scopic salts (e.g. NaCl) giving rise to widespread evidence of deliquescence in the lower tower levels. Evidence indicates that the main factors contributing to accelerated deterioration of interior granite stonework are changes in micro-environmental conditions, salt weathering, chemical weathering through the corrosive effect of strongly alkaline conditions on alumino-silicate minerals within the granite and finally, the mica-rich characteristics of the granite itself which increases its structural and chemical susceptibility to subaerial weathering processes by creating points of weakness within the granite. This case study demonstrates how seemingly minor changes in micro-environmental conditions can unintentionally trigger the rapid and extensive deterioration of a previously stable rock type and threaten the long-term future of nationally iconic opera- tional historic structures.

Wear paths produced by individual hip-replacement patients— A large-scale, long-term follow-up study

Wear particle accumulation is one of the main contributors to osteolysis and implant failure in hip replacements. Altered kinematics produce significant differences in wear rates of hip replacements in simulator studies due to varying degrees of multidirectional motion. Gait analysis data from 153 hip-replacement patients 10-years post-operation were used to model two- and three-dimensional wear paths for each patient. Wear paths were quantified in two dimensions using aspect ratios and in three dimensions using the surface areas of the wear paths, with wear-path surface area correlating poorly with aspect ratio. The average aspect ratio of the patients wear paths was 3.97 (standard deviation ¼ 1.38), ranging from 2.13 to 10.86. Sixty percent of patients displayed aspect ratios between 2.50 and 3.99. However, 13% of patients displayed wear paths with aspect ratios 45.5, which indicates reduced multidirectional motion. The majority of total hip replacement (THR) patients display gait kinematics which produce multidirectional wear paths, but a significant minority display more linear paths.

Behavioral plasticity allows short-term adjustment to a novel environment

Many species are currently experiencing anthropogenically driven environmental changes. Among these changes, increasing noise levels are specifically a problem for species relying on acoustic communication. Recent evidence suggests that some species adjust their acoustic signals to man-made noise. However, it is unknown whether these changes occur through short-term and reversible adjustments by behavioral plasticity or through long-term adaptations by evolutionary change. Using behavioral observations and playback experiments, we show that male reed buntings (Emberiza schoeniclus) adjusted their songs immediately, singing at a higher minimum frequency and at a lower rate when noise levels were high. Our data showed that these changes in singing behavior were short-term adjustments of signal characteristics resulting from behavioral plasticity, rather than a long-term adaptation. However, more males remained unpaired at a noisy location than at a quiet location throughout the breeding season. Thus, phenotypic plasticity enables individuals to respond to environmental changes, but whether these short-term adjustments are beneficial remains to be seen.

Long-term return reversals-Value and growth or tax? UK evidence

This paper examines (i) whether value-growth characteristics have more power than past performance in predicting return reversals; and (ii) whether typical rational behaviour such as incentives to delay paying capital gain taxes can better explain long-term reversals than past performance. We find that value-growth characteristics generally provide better explanations for long-term stock returns than past performance. The evidence also shows that winners identified by capital gains dominate past performance winners in predicting reversals in the cross-sectional comparison. However, in the time-series analysis, when returns on capital gain winners are adjusted by the Fama and French (1996) risk factors, the predictive power of capital gain winners disappears. Our results show that capital gain winners are heavily featured as growth stocks. Return reversals in capital gain winners potentially reflect market price corrections for growth stocks. We conclude that investors’ incentives to delay paying capital gain taxes cannot fully rationalise long-term reversals in the UK market. Our results also imply that the long-term return pattern potentially reflects a mixture of investor rational and irrational behaviour.